Performance in mortality prediction of SAPS 3 And MPM-III scores among adult patients admitted to the ICU of a private tertiary referral hospital in Tanzania: a retrospective cohort study

Abstract

Background Illness predictive scoring systems are significant and meaningful adjuncts of patient management in the Intensive Care Unit (ICU). They assist in predicting patient outcomes, improve clinical decision making and provide insight into the effectiveness of care and management of patients while optimizing the use of hospital resources. We evaluated mortality predictive performance of Simplified Acute Physiology Score (SAPS 3) and Mortality Probability Models (MPM0-III) and compared their performance in predicting outcome as well as identifying disease pattern and factors associated with increased mortality. Methods This was a retrospective cohort study of adult patients admitted to the ICU of the Aga Khan Hospital, Dar- es- Salaam, Tanzania between August 2018 and April 2020. Demographics, clinical characteristics, outcomes, source of admission, primary admission category, length of stay and the support provided with the worst physiological data within the first hour of ICU admission were extracted. SAPS 3 and MPM0-III scores were calculated using an online web-based calculator. The performance of each model was assessed by discrimination and calibration. Discrimination between survivors and non–survivors was assessed by the area under the receiver operator characteristic curve (ROC) and calibration was estimated using the Hosmer-Lemeshow goodness-of-fit test. Results A total of 331 patients were enrolled in the study with a median age of 58 years (IQR 43-71), most of whom were male (n = 208, 62.8%), of African origin (n = 178, 53.8%) and admitted from the emergency department (n = 306, 92.4%). In- hospital mortality of critically ill patients was 16.1%. Discrimination was very good for all models, the area under the receiver-operating characteristic (ROC) curve for SAPS 3 and MPM0-III was 0.89 (95% CI [0.844–0.935]) and 0.90 (95% CI [0.864–0.944]) respectively. Calibration as calculated by Hosmer-Lemeshow goodness-of-fit test showed good calibration for SAPS 3 and MPM0-III with Chi- square values of 4.61 and 5.08 respectively and P–Value > 0.05. Conclusion Both SAPS 3 and MPM0-III performed well in predicting mortality and outcome in our cohort of patients admitted to the intensive care unit of a private tertiary hospital. The in-hospital mortality of critically ill patients was lower compared to studies done in other intensive care units in tertiary referral hospitals within Tanzania.

The Pattern of Admission, Clinical Characteristics, and Outcomes Among Patients Admitted to the Intensive Care Unit of a Tertiary Hospital in Tanzania: A 5-Year Retrospective Review

“… 30 Despite various advances in medical care and life-saving interventions, the Septic shock mortality paradox can be explained by its rapid progression, 31 delayed health-seeking behavior, 32 aging, 33 comorbidities, 31 resistant pathogens 34 and its heterogeneous approach. 35 The in-ICU mortality rate among patients with septic shock at our center was approximately 30%, in line with global 31 and previously conducted studies at our center 4 but much lower when compared to studies done in other parts of Africa. 2 , 3 , 6 , 36 , 37 The infectious disease section of the hospital has made great efforts in setting up a well-equipped laboratory and a comprehensive antibiotic stewardship program able to deliver time-sensitive results and combat antimicrobial resistance.…”

“…Previous findings from the Aga Khan Hospital Dar-es-salaam that looked into the performance of predictive scoring models reported similar findings. 4 Our study results depict a very low ICU mortality rate when compared to similar studies done in Tanzania 2,3 and other countries in Sub-Saharan Africa. [5][6][7][8][9][16][17][18] The discrepancy can be chiefly attributed to the level of care that the hospital provides, which is comparable in various ways to facilities in High-Income Countries (HICs).…”

“…1 Mortality in ICUs remains high even with the utility of the latest and most costly equipment. ICU mortality in many African countries [2][3][4][5][6][7][8][9] both in the public and private sector, is markedly high and exceeds by multiple folds when compared to ICUs in High-Income Countries (HICs). 1,7,10 Documented ICU mortality rates exceeds; 25% in Ethiopia, 5 35% in Tanzania 2,3 and Uganda 9 and approaches 60% in Kenya.…”

“…13 ICU care in Tanzania has been poorly described, with large variations reported in the public and private sectors. [2][3][4] Most ICUs in Tanzania are developed in tertiary and private hospitals in urban areas, not serving most of the population living in rural areas. 14 Given the recent initiatives of the Tanzanian government post-COVID-19 pandemic to increase the critical care capacity in the country, this analysis is timely to serve as an information platform for developing healthcare policies in the region.…”